Modelling osteomyelitis

Pietro Liò,Emanuela Merelli,Kathryn Atwell,Nicola Paoletti,Mohammad Ali Moni,Marco Viceconti

doi:10.1186/1471-2105-13-s14-s12

Pietro Liò, Emanuela Merelli + Show 4 more

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https://doi.org/10.1186/1471-2105-13-s14-s12

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Abstract

BackgroundThis work focuses on the computational modelling of osteomyelitis, a bone pathology caused by bacteria infection (mostly Staphylococcus aureus). The infection alters the RANK/RANKL/OPG signalling dynamics that regulates osteoblasts and osteoclasts behaviour in bone remodelling, i.e. the resorption and mineralization activity. The infection rapidly leads to severe bone loss, necrosis of the affected portion, and it may even spread to other parts of the body. On the other hand, osteoporosis is not a bacterial infection but similarly is a defective bone pathology arising due to imbalances in the RANK/RANKL/OPG molecular pathway, and due to the progressive weakening of bone structure.ResultsSince both osteoporosis and osteomyelitis cause loss of bone mass, we focused on comparing the dynamics of these diseases by means of computational models. Firstly, we performed meta-analysis on a gene expression data of normal, osteoporotic and osteomyelitis bone conditions. We mainly focused on RANKL/OPG signalling, the TNF and TNF receptor superfamilies and the NF-kB pathway. Using information from the gene expression data we estimated parameters for a novel model of osteoporosis and of osteomyelitis. Our models could be seen as a hybrid ODE and probabilistic verification modelling framework which aims at investigating the dynamics of the effects of the infection in bone remodelling. Finally we discuss different diagnostic estimators defined by formal verification techniques, in order to assess different bone pathologies (osteopenia, osteoporosis and osteomyelitis) in an effective way.ConclusionsWe present a modeling framework able to reproduce aspects of the different bone remodeling defective dynamics of osteomyelitis and osteoporosis. We report that the verification-based estimators are meaningful in the light of a feed forward between computational medicine and clinical bioinformatics.

Highlights

This work focuses on the computational modelling of osteomyelitis, a bone pathology caused by bacteria infection
With respect to control cases, for the microarray platform GPL96, 22 genes related to RANKL, RANK, OPG, NF-kB proteins, TNF and TNF receptor superfamilies are over expressed and 13 genes are down regulated in osteomyelitis
In particular we extended it in order to explicitly simulate bone pathologies: osteoporosis is reproduced by including an ageing factor that decreases the death rates of cells and by including a factor that increases the RANKL expression; osteomyelitis is modelled by adding a state variable for bacteria that affects the autocrine and paracrine regulation factors of osteoblasts and osteoclasts, to Ayati’s model on bone myeloma [16]

Summary

Introduction

This work focuses on the computational modelling of osteomyelitis, a bone pathology caused by bacteria infection (mostly Staphylococcus aureus). The infection alters the RANK/RANKL/OPG signalling dynamics that regulates osteoblasts and osteoclasts behaviour in bone remodelling, i.e. the resorption and mineralization activity. Trabecular ( known as cancellous or “spongy”) tissue is located beneath the compact bone and consists of a meshwork of bony bars (trabeculae) with many interconnecting spaces containing bone marrow. Both bone tissues undergo a continuous remodelling dynamics where old bone is replaced by new tissue ensuring the mechanical integrity. While osteoblasts and osteoclasts are located in the fluid part of the BMU, another type of cells, the osteocytes, are trapped in the bone matrix and they play a relevant role in the remodelling process. The number of BMUs, the bone resorption rate, and the bone formation rate are all relatively constant [3]

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